The development of highly efficient production systems able to minimize production costs and improve productivity and product quality is universally recognized as one of the central themes of Smart Manufacturing, particularly in the context of the Industry 4.0 vision. Highly efficient production is essential for the competitiveness of all companies wanting to achieve improved performance, and to differentiate themselves from low-cost countries through the production of high quality products, an aspect that is particularly significant for the Veneto manufacturing sector. Furthermore, systems with high application flexibility can maintain their efficiency even in the face of extreme variability in demand, while reducing waste (also for environmental sustainability) and the energy consumption resulting from inefficient manufacturing processes (energy efficiency). In this light, it is necessary to develop integrated methodologies, technologies and tools for maintenance, quality control, and production logistics.
The PreMANI project aims to demonstrate the applicability of these techniques across disparate application domains, characterized by very different needs, by leveraging methodological aspects of a general nature.
The project will develop techniques to predict the operating characteristics of machines and plants by combining quality analysis (of the product) with efficiency analysis (of the plants), within a context described as Predictive Manufacturing. The developed solutions pertain to the realm of Digital Manufacturing and include the creation of advanced tools for decision support, hardware components (dedicated sensor architectures, low-cost embedded systems for real-time use of complex prediction models), infrastructural components (cloud-based IT platforms), and algorithmic elements (with particular emphasis on the use of machine learning techniques).
Innovation
The project is particularly challenging given the diversity of application areas. In fact, the industrial sectors in question represent paradigmatic examples of operating environments in which increasing intelligence ("smartness") is required of individual machines that must operate in interconnected environments (mechanical-textile, packaging, precision machining), and in complex and articulated processing systems (foundries, large-scale industrial production, food production systems).
Partners
CIELLE SRL, EDALAB SRL, ELECTROLUX ITALIA SPA, ENGINSOFT SPA, FONDERIA CORRÀ SPA, GALDI SRL, M3E ERL, M31 ITALIA SRL, RDS MOULDING TECHNOLOGY SPA, SIMNUMERICA SRL, SMIT SRL, SORDATO SRL, STATWOLF DATA SCIENCE SRL, T2I - TRASFERIMENTO TECNOLOGICO E INNOVAZIONE SCARL, UNIVERSITÀ DEGLI STUDI DI PADOVA, UNIVERSITÀ DEGLI STUDI DI VERONA, ZANARDI FONDERIE SPA.
Funding Scheme
POR - Obiettivo "Incremento dell'attività di innovazione delle imprese" - Parte FESR fondo europeo di sviluppo regionale 2014 - 2020
“Progetto finanziato con il POR FESR 2014-2020 Regione del Veneto” - ASSE 1 “RICERCA, SVILUPPO TECNOLOGICO E INNOVAZIONE” AZIONE 1.1.4 “Sostegno alle attività collaborative di R&S per lo sviluppo di nuove tecnologie sostenibili, di nuovi prodotti e servizi”
Project co-funded by POR ERDF 2014-2020 Regione del Veneto" - AXIS 1 "RESEARCH, TECHNOLOGICAL DEVELOPMENT AND INNOVATION" ACTION 1.1.4 "Support for collaborative R&D activities for the development of new sustainable technologies, new products and services"
Funding: € 2.999.858,64 / 64 / Grant Amount: € 2.999.858,64
| Start date: | 07-11-2017 |
| End date: | 30-12-2020 |
| Total budget - Public funding: | 5 396 160,00 Euro - 2 999 858,00 Euro |
